CUDA C compiler targets x86 platforms

STMicroelectronics subsidiary The Portland Group reports the development of a CUDA C compiler that will work for systems based on general-purpose 64- and 32-bit x86 architectures.

The NVIDIA CUDA architecture was developed to enable offloading computationally intensive kernels to massively parallel GPUs. Through function calls and language extensions, CUDA gives developers explicit control over the mapping of general-purpose computational kernels to GPUs, as well as the placement and movement of data between an x86 processor and the GPU.

The PGI CUDA C compiler for x86 platforms will allow developers using CUDA to compile and optimize CUDA applications to run on x86-based workstations, servers and clusters with or without an NVIDIA GPU accelerator. When run on x86-based systems without a GPU, PGI CUDA C applications will use multiple cores and the streaming SIMD (Single Instruction Multiple Data) capabilities of Intel and AMD CPUs for parallel execution.

PGI offers two programming models for GPU accelerators. PGI Accelerator is a high-level directive-based programming model targeting scientific and engineering-domain experts working in high-performance computing. PGI Accelerator compilers are currently available for C99 and Fortran 95/2003. CUDA Fortran, a Fortran 95/2003 analog to NVIDIA CUDA C, was developed by PGI in cooperation with NVIDIA in 2009. CUDA Fortran allows expert programmers to control aspect of GPU programming.